Get Instant Access
to This Blueprint

Cio icon

Build Your Generative AI Roadmap

Generative AI is here, and it’s time to find its best uses – systematically and responsibly.

Generative AI has made a grand entrance, presenting opportunities and causing disruption across organizations and industries. Moving beyond the hype, it’s imperative to build and implement a strategic plan to adopt generative AI and outpace competitors.

Yet generative AI has to be done right because the opportunity comes with risks and the investments have to be tied to outcomes.

Adopt a human-centric and value-based approach to generative AI

IT and business leaders will need to be strategic and deliberate to thrive as AI adoption changes industries and business operations.

  • Establish responsible AI guiding principles: Address human-based requirements to govern how generative AI applications are developed and deployed.
  • Align generative AI initiatives to strategic drivers for the organization: Assess generative AI opportunities by seeing how they align to the strategic drivers of the organization. Examples of strategic drivers include increasing revenue, reducing costs, driving innovation, and mitigating risk.
  • Measure and communicate effectively: Have clear metrics in place to measure progress and success of AI initiatives and communicate both policies and results effectively.

Build Your Generative AI Roadmap Research & Tools

1. Build Your Generative AI Roadmap Deck – A step-by-step document that walks you through how to leverage generative AI and align with the organization’s mission and objectives to increase revenue, reduce costs, accelerate innovation, and mitigate risk.

This blueprint outlines how to build your generative AI roadmap, establish responsible AI principles, prioritize opportunities, and develop policies for usage. Establishing and adhering to responsible AI guiding principles provides safeguards for the adoption of generative AI applications.

2. AI Maturity Assessment and Roadmap Tool – Develop deliverables that will be milestones in creating your organization’s generative AI roadmap for implementing candidate applications.

This tool provides guidance for developing the following deliverables:

  • Responsible AI guiding principles
  • Current AI maturity
  • Prioritized candidate generative AI applications
  • Generative AI policies
  • Generative AI roadmap

3. The Era of Generative AI C‑Suite Presentation – Develop responsible AI guiding principles, assess AI capabilities and readiness, and prioritize use cases based on complexity and alignment with organizational goals and responsible AI guiding principles.

This presentation template uses sample business capabilities (use cases) from the Marketing & Advertising business capability map to provide examples of candidates for generative AI applications. The final executive presentation should highlight the value-based initiatives driving generative AI applications, the benefits and risks involved, how the proposed generative AI use cases align to the organization’s strategy and goals, the success criteria for the proofs of concept, and the project roadmap.

Member Testimonials

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.


Overall Impact


Average $ Saved


Average Days Saved




$ Saved

Days Saved

Werner Co.

Guided Implementation




I thoroughly enjoyed and appreciated Altaz's command of the AI Landscape. His perspective and guidance are helping validate our approach and ident... Read More

Hy Cite Enterprises, LLC

Guided Implementation




Great overview and impromptu questions from us to Irina. Thanks!

Pima County Community College District

Guided Implementation




Altaz knows his stuff! As always, Info-Tech makes it simple.

Office of the Superintendent of Financial Institutions Canada





The facilitator Denis was fantastic. He kept the workshop on track and came prepared everyday. I have worked with him a few times now and would say... Read More

Canada Revenue Agency





Township of King

Guided Implementation




Altaz is extremely knowledgeable in AI. We gain much insights from this session. Thank you!

The Pittsburgh Water and Sewer Authority

Guided Implementation





Guided Implementation




The process and methodology that Altaz took me through today was excellent.

Calvert County Government

Guided Implementation




Oregon Youth Authority

Guided Implementation




Bill is a fantastic presenter and very knowledgeable in the field of AI. He was able to answer all of my questions and left me wanting to know mor... Read More


Guided Implementation




City of Lake Oswego

Guided Implementation




Altaz explained the slide is such away that everything just clicked and started to make more sense.

Department of State Development Infrastructure Local Government and Planning

Guided Implementation





Guided Implementation




Great experience overall. I truly appreciate being able to talk with an expert - Natalia brings so much experience and expertise to the conversat... Read More

City of Burbank

Guided Implementation




Treace Medical Concepts, Inc.

Guided Implementation




Began with a clear objective, ended meeting the objective

Heritage Petroleum Co Ltd

Guided Implementation




Guidehouse LLP

Guided Implementation




Imprint Consulting Limited, T/A Org

Guided Implementation




Extremely valuable session, too be honest it is hard to measure the value at this time as we are in Discovery mode, figuring out the roadmaps and w... Read More

IMA Financial Group, Inc.

Guided Implementation




Build Your Generative AI Roadmap

Leverage the power of generative AI to improve business outcomes.

Analyst Perspective

We are entering the era of generative AI. This is a unique time in our history where the benefits of AI are easily accessible and becoming pervasive, with copilots emerging in the major business tools we use today. The disruptive capabilities that can potentially drive dramatic benefits also introduce risks that need to be planned for.

A successful business-driven generative AI roadmap requires:

  • Establishing responsible AI guiding principles to guide the development and deployment of generative AI applications.
  • Assess generative AI opportunities by using criteria based on the organization's mission and objectives, responsible AI guiding principles, and the complexity of the initiative.
  • Communicating, educating on, and enforcing generative AI usage policies.

Bill Wong, Principal Research Director

Bill Wong
Principal Research Director
Info-Tech Research Group

Executive Summary

Your Challenge Common Obstacles Solution

Generative AI is disrupting all industries and providing opportunities for organization-wide advantages.

Organizations need to understand this disruptive technology and trends to properly develop a strategy for leveraging this technology successfully.

  • Generative AI requires alignment to a business strategy.
  • IT is an enabler and needs to align with and support the business stakeholders.
  • Organizations need to adopt a data-driven culture.

All organizations, regardless of size, should be planning how to respond to this new and innovative technology.

Business stakeholders need to cut through the hype surrounding generative AI like ChatGPT to optimize investments for leveraging this technology to drive business outcomes.

  • Understand the market landscape, benefits, and risks associated with generative AI.
  • Plan for responsible AI.
  • Understand the gaps the organization needs to address to fully leverage generative AI.

Without a proper strategy and responsible AI guiding principles, the risks to deploying this technology could negatively impact business outcomes.

Info-Tech's human-centric, value-based approach is a guide for deploying generative AI applications and covers:

  • Responsible AI guiding principles
  • AI Maturity Model
  • Prioritizing candidate generative AI-based use cases
  • Developing policies for usage

This blueprint will provide the list of activities and deliverables required for the successful deployment of generative AI solutions.

Info-Tech Insight
Create awareness among the CEO and C-suite of executives on the potential benefits and risks of transforming the business with generative AI.

Key concepts

Artificial Intelligence (AI)
A field of computer science that focuses on building systems to imitate human behavior, with a focus on developing AI models that can learn and can autonomously take actions on behalf of a human.

AI Maturity Model
The AI Maturity Model is a useful tool to assess the level of skills an organization has with respect to developing and deploying AI applications. The AI Maturity Model has multiple dimensions to measure an organization's skills, such as AI governance, data, people, process, and technology.

Responsible AI
Refers to guiding principles to govern the development, deployment, and maintenance of AI applications. In addition, these principles also provide human-based requirements that AI applications should address. Requirements include safety and security, privacy, fairness and bias detection, explainability and transparency, governance, and accountability.

Generative AI
Given a prompt, a generative AI system can generate new content, which can be in the form of text, images, audio, video, etc.

Natural Language Processing (NLP)
NLP is a subset of AI that involves machine interpretation and replication of human language. NLP focuses on the study and analysis of linguistics as well as other principles of artificial intelligence to create an effective method of communication between humans and machines or computers.

An AI-powered chatbot application built on OpenAI's GPT-3.5 implementation, ChatGPT accepts text prompts to generate text-based output.

Your challenge

This research is designed to help organizations that are looking to:

  • Establish responsible AI guiding principles to address human-based requirements and to govern the development and deployment of the generative AI application.
  • Identify new generative AI-enabled opportunities to transform the work environment to increase revenue, reduce costs, drive innovation, or reduce risk.
  • Prioritize candidate use cases and develop generative AI policies for usage.
  • Have clear metrics in place to measure the progress and success of AI initiatives.
  • Build the roadmap to implement the candidate use cases.

Common obstacles

These barriers make these goals challenging for many organizations:

  • Getting all the right business stakeholders together to develop the organization's AI strategy, vision, and objectives.
  • Establishing responsible AI guiding principles to guide generative AI investments and deployments.
  • Advancing the AI maturity of the organization to meet requirements of data and AI governance as well as human-based requirements such as fairness, transparency, and accountability.
  • Assessing generative AI opportunities and developing policies for use.

Info-Tech's definition of an AI-enabled business strategy

  • A high-level plan that provides guiding principles for applications that are fully driven by the business needs and capabilities that are essential to the organization.
  • A strategy that tightly weaves business needs and the applications required to support them. It covers AI architecture, adoption, development, and maintenance.
  • A way to ensure that the necessary people, processes, and technology are in place at the right time to sufficiently support business goals.
  • A visionary roadmap to communicate how strategic initiatives will address business concerns.

An effective AI strategy is driven by the business stakeholders of the organization and focused on delivering improved business outcomes.

This blueprint in context

This guidance covers how to create a tactical roadmap for executing generative AI initiatives


  • This blueprint is not a proxy for a fully formed AI strategy. Step 1 of our framework necessitates alignment of your AI and business strategies. Creation of your AI strategy is not within the scope of this approach.
  • This approach sets the foundations for building and applying responsible AI principles and AI policies aligned to corporate governance and key regulatory obligations (e.g. privacy). Both steps are foundational components of how you should develop, manage, and govern your AI program but are not a substitute for implementing broader AI governance.

Guidance on how to implement AI governance can be found in the blueprint linked below.

Tactical Plan

Download our AI Governance blueprint

Measure the value of this blueprint

Leverage this blueprint's approach to ensure your generative AI initiatives align with and support your key business drivers

This blueprint will guide you to drive and improve business outcomes. Key business drivers will often focus on:

  • Increasing revenue
  • Reducing costs
  • Improving time to market
  • Reducing risk

In phase 1 of this blueprint, we will help you identify the key AI strategy initiatives that align to your organization's goals. Value to the organization is often measured by the estimated impact on revenue, costs, time to market, or risk mitigation.

In phase 4, we will help you develop a plan and a roadmap for addressing any gaps and introducing the relevant generative AI capabilities that drive value to the organization based on defined business metrics.

Once you implement your 12-month roadmap, start tracking the metrics below over the next fiscal year (FY) to assess the effectiveness of measures:

Business Outcome Objective Key Success Metric
Increasing Revenue Increased revenue from identified key areas
Reducing Costs Decreased costs for identified business units
Improving Time to Market Time savings and accelerated revenue adoption
Reducing Risk Cost savings or revenue gains from identified business units

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit Guided Implementation Workshop Consulting
"Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful." "Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track." "We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place." "Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project."

Diagnostics and consistent frameworks are used throughout all four options.

Guided Implementation

What does a typical GI on this topic look like?

Phase 1 Phase 2 Phase 3 Phase 4

Call #1: Scope requirements, objectives, and your specific challenges.

Call #2: Identify AI strategy, vision, and objectives.

Call #3: Define responsible AI guiding principles to adopt and identify current AI maturity level. Call #4: Assess and prioritize generative AI initiatives and draft policies for usage.

Call #5: Build POC implementation plan and establish metrics for POC success.

Call #6: Build and deliver executive-level generative AI presentation.

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is between 5 to 8 calls over the course of 1 to 2 months.

AI Roadmap Workshop Agenda Overview

Contact your account representative for more information. 1-888-670-8889

Session 1 Session 2 Session 3 Session 4
Establish Responsible AI Guiding Principles Assess AI Maturity Prioritize Opportunities and Develop Policies Build Roadmap
Trends Consumer groups, organizations, and governments around the world are demanding that AI applications adhere to human-based values and take into consideration possible impacts of the technology on society. Leading organizations are building AI models guided by responsible AI guiding principles. Organizations delivering new applications without developing policies for use will produce negative business outcomes. Developing a roadmap to address human-based values is challenging. This process introduces new tools, processes, and organizational change.
  • Focus on working with executive stakeholders to establish guiding principles for the development and delivery of new applications.
  • Assess the organization's current capabilities to deliver AI-based applications and address human-based requirements.
  • Leverage business alignment criteria, responsible AI guiding principles, and project characteristics to prioritize candidate uses cases and develop policies.
  • Build the implementation plan, POC metrics, and success criteria for each candidate use case.
  • Build the roadmap to address the gap between the current and future state and enable the identified use cases.
  • Understanding of external legal and regulatory requirements and organizational values and goals.
  • Risk assessment of the proposed use case and a plan to monitor its impact.
  • Assessment of the organization's current AI capabilities with respect to its AI governance, data, people, process, and technology infrastructure.
  • Criteria to assess candidate use cases by evaluating against the organization's mission and goals, the responsible AI guiding principles, and complexity of the project.
  • Risk assessment for each proposed use case
  • POC implementation plan for each candidate use case
  1. Foundational responsible AI guiding principles
  2. Additional customized guiding principles to add for consideration
  1. Current level of AI maturity, resources, and capacity
  1. Prioritization of opportunities
  2. Generative AI policies for usage
  1. Roadmap to a target state that enables the delivery of the prioritized generative AI use cases
  2. Executive presentation

Insight summary

Overarching Insight
Build your generative AI roadmap to guide investments and deployment of these solutions.

Responsible AI
Assemble the C-suite to make them aware of the benefits and risks of adopting generative AI-based solutions.

  • Establish responsible AI guiding principles to govern the development and deployment of generative AI applications.

AI Maturity Model
Assemble key stakeholders and SMEs to assess the challenges and tasks required to implement generative AI applications.

  • Assess current level of AI maturity, skills, and resources.
  • Identify desired AI maturity level and challenges to enable deployment of candidate use cases.

Opportunity Prioritization
Assess candidate business capabilities targeted for generative AI to see if they align to the organization's business criteria, responsible AI guiding principles, and capabilities for delivering the project.

  • Develop prioritized list of candidate use cases.
  • Develop policies for generative AI usage.

Tactical Insight
Identify the gaps needed to address deploying generative AI successfully.

Tactical Insight
Identify organizational impact and requirements for deploying generative AI applications.

Key takeaways for developing an effective business-driven generative AI roadmap

Align the AI strategy with the business strategy

Create responsible AI guiding principles, which are a critical success factor

Evolve AI maturity level by focusing on principle-based requirements

Develop criteria to assess generative AI initiatives

Develop generative AI policies for use

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

AI Maturity Assessment & Roadmap Tool
Use our best-of-breed AI Maturity Framework to analyze the gap between your current and target states and develop a roadmap aligned with your value stream to close the gap.

The Era of Generative AI C-Suite Presentation
Present your AI roadmap in a prepopulated document that summarizes all the key findings of this blueprint and provides your C-suite with a view of the AI challenge and your plan of action to meet it.

Our AI Maturity Assessment & Roadmap and The Era of Generative AI C-Suite Presentation tools enable you to shape your generative AI roadmap and communicate the deliverables to your C-suite sponsors in terms of the value of initiatives.

Artificial Intelligence Index Report - Key Findings

CEOs , CIOs, and business leaders are struggling with many questions surrounding the adoption of generative AI

November 30, 2022
OpenAI releases ChatGPT

ChatGPT is a large language model, or an AI-based chatbot, that became so popular it reached 100 million monthly active users in just two months.

This made it the fastest-growing consumer application in history. The launch of this generative AI application has created a frenzy of interest and activity across all industries. Organizations are rushing to understand how to leverage this innovation and, at the same time, manage the new risks and disruptions generative AI introduces.

  • Generative AI breaks into the public consciousness.
  • AI systems become more flexible.
  • Generative models have arrived and so have their ethical problems.
  • The number of incidents concerning the misuse of AI is rapidly rising.
  • Interest in AI ethics continues to skyrocket.
  • The legal world is waking up to AI.

When Stanford asked ChatGPT to explain why it is significant, this was ChatGPT's response:
ChatGPT is significant because it is a highly advanced Al language model developed by OpenAI, which can generate human-like text responses to questions and prompts. Its large-scale training on diverse text data and its cutting-edge deep learning architecture make it capable of generating informative and coherent responses to a wide range of topics, making it useful for various NLP applications such as chatbots, content generation, and language translation. Additionally, its open-source availability allows for further research and development in the field of Al language processing.

Source: Stanford

AI overview

AI definitions


  • Artificial intelligence (AI) is human intelligence mimicked by machine algorithms. Examples: Playing Chess or Go.
  • Machine learning (ML) is a subset of AI algorithms to parse data, learn from data, and then make a determination or prediction. Example: spam detection, preventative maintenance.
  • Deep learning (DL) is a subset of machine learning algorithms that leverage artificial neural networks to develop relationships among the data. Examples: image classification, facial recognition, generative AI.

What Makes AI Perform

What Makes AI Different

Generative AI gives very human-like responses to general queries, and its capabilities are growing exponentially

Large language models power generative AI

Transformer-Based Large Language Models

Conventional AI

  • Conventional neural networks
    • Process data sequentially
  • Input total string of text
  • Good for applications not needing to understanding context or relationships

Generative AI

  • Transformer-based neural networks
    • Can process data in parallel
  • Attention-based inputs
  • Able to create new human-like responses

Benefits/Use Cases

  • Chatbots for member service and support
  • Writing email responses, resumes, and papers
  • Creating photorealistic art
  • Suggesting new drug compounds to test
  • Designing physical products and buildings
  • And more...

Generative AI is transforming all industries

Financial Services
Create more engaging customer collateral by generating personalized correspondence based on previous customer engagements. Collect and aggregate data to produce insights into the behavior of target customer segments.

Retail Generate unique, engaging, and high-quality marketing copy or content, from long-form blog posts or landing pages to SEO-optimized digital ads, in seconds.

Generate new designs for products that comply to specific constraints, such as size, weight, energy consumption, or cost.

Transform the citizen experience with chatbots or virtual assistants to assist people with a wide range of inquiries, from answering frequently asked questions to providing personalized advice on public services.

The global generative AI market size reached US $10.3 billion in 2022. Looking forward, forecasts estimate growth to US $30.4 billion by 2028, 20.01% compound annual growth rate (CAGR).

Source: IMARC Group

Generative AI is here, and it’s time to find its best uses – systematically and responsibly.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.


Overall Impact

Average $ Saved

Average Days Saved

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve.

Read what our members are saying

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

You Get:

  • A four-phased detailed model from building responsible guiding principles to an execution roadmap.
  • A deep understanding of the generative AI landscape, risks, and opportunities.
  • Case studies and industry-specific capability maps for AI adoption.

Need Extra Help?
Speak With An Analyst

Get the help you need in this 4-phase advisory process. You'll receive 6 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Establish responsible AI guiding principles
  • Call 1: ​Scope requirements, objectives, and your specific challenges.
  • Call 2: Identify AI strategy, vision, and objectives.

Guided Implementation 2: Assess current level of AI maturity
  • Call 1: Define responsible AI guiding principles to adopt and identify current AI maturity level.

Guided Implementation 3: Prioritize candidate opportunities and develop policies
  • Call 1: Assess and prioritize generative AI initiatives and draft policies for usage.

Guided Implementation 4: Build and communicate the roadmap
  • Call 1: Build POC implementation plan and establish metrics for POC success.
  • Call 2: Build and deliver executive-level generative AI presentation.


Bill Wong

Visit our Exponential IT Research Center
Over 100 analysts waiting to take your call right now: 1-519-432-3550 x2019